cs-foundations
Master discrete mathematics, logic, formal proofs, and computational thinking. Build the mathematical foundation for all computer science.
Best use case
cs-foundations is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Master discrete mathematics, logic, formal proofs, and computational thinking. Build the mathematical foundation for all computer science.
Teams using cs-foundations should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cs-foundations/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cs-foundations Compares
| Feature / Agent | cs-foundations | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Master discrete mathematics, logic, formal proofs, and computational thinking. Build the mathematical foundation for all computer science.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# CS Foundations Skill
## Skill Metadata
```yaml
skill_config:
version: "1.0.0"
category: theoretical
prerequisites: []
estimated_time: "6-8 weeks"
difficulty: intermediate
parameter_validation:
topic:
type: string
enum: [logic, proofs, sets, functions, combinatorics, number-theory, graphs]
required: true
depth:
type: string
enum: [intro, standard, advanced]
default: standard
retry_config:
max_attempts: 3
backoff_strategy: exponential
initial_delay_ms: 500
observability:
log_level: INFO
metrics: [topic_usage, proof_verification_rate, exercise_completion]
```
---
## Quick Start
Computer science is built on mathematics. Master these fundamentals:
### Core Topics
**Discrete Mathematics**
- Set theory and operations
- Logic and proof techniques
- Combinatorics and counting
- Number theory basics
- Relations and functions
**Computational Thinking**
- Problem decomposition
- Abstraction and generalization
- Pattern recognition
- Algorithmic thinking
**Formal Logic**
- Propositional logic
- Predicate logic
- Proof by induction
- Truth tables and logical equivalence
---
## Learning Path
**Week 1: Logic Basics**
- Boolean algebra
- Truth tables
- Logical operators
- Inference rules
**Week 2: Proof Techniques**
- Direct proof
- Proof by contradiction
- Mathematical induction
- Strong induction
**Week 3: Set Theory**
- Set operations (∪, ∩, complement)
- Cartesian product
- Relations
- Equivalence relations
**Week 4: Functions**
- Function notation
- Domain, codomain, range
- One-to-one and onto
- Function composition
**Week 5: Combinatorics**
- Counting principles
- Permutations
- Combinations
- Pigeonhole principle
**Week 6: Number Theory**
- Modular arithmetic
- Prime numbers
- GCD and Euclidean algorithm
- Congruence
---
## Practice Problems
1. Prove by induction that 1+2+...+n = n(n+1)/2
2. Prove √2 is irrational
3. Show A ∪ (B ∩ C) = (A ∪ B) ∩ (A ∪ C)
4. Count functions from {1,2,3} to {a,b}
5. Solve: x ≡ 5 (mod 12) and x ≡ 3 (mod 8)
---
## Troubleshooting
| Issue | Root Cause | Resolution |
|-------|------------|------------|
| Proof stuck | Missing case or wrong direction | Check base case, verify induction step |
| Set operation confusion | ∪ vs ∩ mix-up | Draw Venn diagram |
| Counting error | Overcounting duplicates | Distinguish P(n,r) vs C(n,r) |
| Modular arithmetic error | Forgot wraparound | Work with remainders explicitly |
---
## Key Concepts
- **Axioms**: Statements we assume true
- **Theorems**: Statements we prove
- **Lemmas**: Helper theorems
- **Corollaries**: Results that follow easily
---
## Why It Matters
These foundations enable:
- Understanding algorithm correctness
- Analyzing computational complexity
- Designing new algorithms
- Proving algorithm properties
- Understanding what's computable
---
## Interview Prep
- Explain mathematical induction
- Prove that a function is injective
- Count permutations with constraints
- Solve modular equations
- Apply pigeonhole principleRelated Skills
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